DocumentCode
648460
Title
Design of an online intelligent alarming system for cascading failures of group of wind farms
Author
Jianan Mu ; Hongbin Sun ; Qinglai Guo ; Wenchuan Wu ; Fengda Xu ; Boming Zhang
Author_Institution
Dept. of Electr. Eng., Tsinghua Univ., Beijing, China
fYear
2013
fDate
21-25 July 2013
Firstpage
1
Lastpage
5
Abstract
In China, large-scale wind power is integrated to the power grid in a concentrating way by connecting a group of wind farms together. Each wind farm is consisted of hundreds of wind turbines and covers a large geographical area. However, such a system is vulnerable to occasional faults which can easily develop into cascading failures of adjacent wind farms, making the wind farms lose most of their power in a very short time. Cascading failures have occurred several times in reality. It is urgently necessary to construct an online assistant system to detect, analyze and explain the cascading events timely and effectively. Given that Phasor Measurement Units (PMUs) are widely installed in Chinese wind farms, the dynamic process can be recorded effectively, supplemented with Supervisory Control and Data Acquisition system (SCADA) signals. In this paper, a conceptual design of an online intelligent alarming system for cascading failures of wind farms based on PMUs and SCADA is introduced. The system is justified using real data collected in wind farms.
Keywords
SCADA systems; phasor measurement; power grids; wind power plants; wind turbines; Chinese wind farm; PMU; SCADA; cascading failure; online assistant system; online intelligent alarming system; phasor measurement unit; power grid; supervisory control and data acquisition system signal; wind turbine; Phasor measurement units; Power system faults; Power system protection; Reactive power; Substations; Wind farms; Wind turbines; PMU; SCADA; cascading failures; intelligent alarming; wind farm;
fLanguage
English
Publisher
ieee
Conference_Titel
Power and Energy Society General Meeting (PES), 2013 IEEE
Conference_Location
Vancouver, BC
ISSN
1944-9925
Type
conf
DOI
10.1109/PESMG.2013.6673043
Filename
6673043
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